An approach for investigating the dynamics of physiological time series is presented
namely the symbolic dynamics analyzing the reconstructed phase space. Since physiological time series are usually nonstationary
to remove the time varying local mean and extract the wave characteristics of the time series
all the vectors in the reconstructed phase space are normalized to be endowed with the same mean and standard deviation. The maximum topological entropy(MTE)criterion is then introduced to find a partition for the phase space. The tested results on the logistic map and the signals of postural stability show that the MTE criterion provides a partition closer to the optimal partition than a partition leading to equiprobable symbols. Two measures from symbolic dynamics are used to characterize the dynamics of the time series. The calculated results for the signals of postural stability show that this approach enables to detect the dissimilarity of physiological time series in different physiological states.
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